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Where Will Man Take Us?

The Bold Story of the Man Technology is Creating

By Atul Jalan
15-minute read
Audio available
Where Will Man Take Us?: The Bold Story of the Man Technology is Creating by Atul Jalan

Where Will Man Take Us? (2019) explores how, thanks to rapid technological advances, humanity has come to stand on the cusp of a great leap forward. In just decades, our economy, health and perhaps even our biology will be transformed; these blinks explore these developments and the difficult ethical and societal questions they pose.

  • Mortals who hope one day to achieve immortality
  • People who’d like to get to grips with the latest tech developments
  • Big thinkers interested in the future of humanity and human society

Atul Jalan is the founder of Manthan Systems, a successful AI data analytics software firm based in Bangalore, India. Long fascinated by technology, Jalan takes a passionate interest in artificial intelligence, big data analytics and the coming machine age.

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Where Will Man Take Us?

The Bold Story of the Man Technology is Creating

By Atul Jalan
  • Read in 15 minutes
  • Audio & text available
  • Contains 9 key ideas
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Where Will Man Take Us?: The Bold Story of the Man Technology is Creating by Atul Jalan
Synopsis

Where Will Man Take Us? (2019) explores how, thanks to rapid technological advances, humanity has come to stand on the cusp of a great leap forward. In just decades, our economy, health and perhaps even our biology will be transformed; these blinks explore these developments and the difficult ethical and societal questions they pose.

Key idea 1 of 9

Artificial intelligence is improving through learning, and machines are becoming more cognitive.

In 1997, Deep Blue, an IBM supercomputer, beat the legendary chess player Gary Kasparov in a six-game series. It was a major step forward for artificial intelligence. But it was possible because chess is a relatively finite game, based on clear rules. Teach a machine the rules, and you can teach it to win.

So far, artificial intelligence has been good at performing individual tasks like playing chess. It can, as Apple’s Siri demonstrates, learn to understand your voice and follow commands; it can even translate one language into another.

But so far, it hasn’t learned to replicate wider human intelligence effectively. Things that come naturally to us, like intuition or creativity, remain difficult for machines. That’s starting to change, however, as the game Go shows us.

Go is a fantastically complicated two-player board game in which you try to surround more territory than your competitor. At any given time in a game of chess, there is an average of 35 possible moves available. In Go, there are 250. There are 361 squares on a Go grid, compared to 64 in chess, and an incredible 10170 potential board configurations. That’s too many to really comprehend, but for perspective, it’s far more than the number of atoms in our universe.

So when you play Go, you have to rely more on human intuition and feel than logical, rule-based decisions. It just isn’t possible to do all the calculations. That’s why when AlphaGo, an artificial intelligence created by Google’s DeepMind research unit, beat Lee Sedol, a top player of the game, it was clear that we’re on the cusp of major advances. But how did AlphaGo succeed?

Well, DeepMind gave it a collection of 30 million moves collected from human players and then trained it to play. The machine was then programmed for reinforcement learning, which mimics the way that our brains work. That meant that the artificial intelligence collected points when it did something that proved to be correct and lost them when it made mistakes. Then DeepMind trained AlphaGo against different versions of itself. Each time it played a game, it would learn by remembering which move brought it a reward, creating a cycle of improvement.

Observers of AlphaGo commented that its moves were inventive, with seasoned players even describing some as “divine.” Clearly, machines are becoming more human, developing intuition and creativity. Rather than being programmed, as with the rules of chess, they are teaching themselves to learn. And this shift is getting faster.

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